Scientific Aim of the Project

The GRAPE (General Relativistic Astrometry and Pulsar Experiment) project aims to detect and characterize nano-Hertz gravitational waves (GWs). It proposes a novel, joint analysis of two independent European datasets:

• Precision timing of millisecond pulsars from the European Pulsar Timing Array (EPTA).

• High-precision astrometry of approximately two billion stars from the Gaia mission (ESA).

The ultimate goal is to provide the first-ever joint constraint on the Gravitational Wave Background (GWB) and individual supermassive black hole binaries.

INAF Unit Expertise and Assigned WPs 

The INAF (National Institute for Astrophysics) unit, based at the Astrophysical Observatory of Turin (OATo), serves as a center of excellence for relativistic astrometry. The INAF-OATo astrometric group is a key player in the Gaia Data Processing and Analysis Consortium (DPAC) and supervises the Gaia Data Processing Center of Torino (DPCT) hosted in ALTEC with the support of ASI.

Within the GRAPE project, our mission is to transform the Milky Way into a vast gravitational wave detector by extracting GW signals of ultra-low frequencies from the Gaia mission datasets.

Our expertise includes:

• Implementation of high accurate general relativistic models (RAMOD) for the inverse ray tracing to provide the necessary measurement toolkit in GR for high-precision astrometry. The framework includes models for light propagation in both the static and dynamical gravitational fields of the Solar System, as well as a GR-compliant observer. The INAF unit is responsible for the theoretical comparison between RAMOD and other relativistic models, such as GREM (Gaia Relativistic Model), to ensure the highest level of accuracy in data analysis and processing. General relativistic models for Gaia serve as model of weak GR effects and provide the primary architecture of the astrometric gravitational wave (GW)  detection strategy. GWs are time-dependent perturbations of spacetime geometry that may alter the null geodesics of photons from stars to the Gaia satellite. GWs leave a specific fingerprint in the apparent location and motions of stars.

• Implementation of differential astrometric techniques from global astrometry. Based on the  GAREQ experiment to test GR by discriminating the light deflection caused by Jupiter's monopole and quadrupolar mass distribution, we demonstrated the framework's ability to handle high-order relativistic effects that are critical for the sensitive measurements required by GRAPE.

• Handling and calibrating systematic errors in the massive satellite datasets.

• Developing the theoretical framework to identify GW astrometric signals with new observations and in astrometric residuals. Any unexplained "fluctuations" in these residuals, after accounting for all known relativistic effects, are potential signatures of incoming gravitational waves.

Assigned Work Packages:

• WP1: Preparation and integration of the Gaia dataset. This involves extracting and cleaning the data to make it suitable for GW searches.

• WP2: Collaborating on the development of the joint EPTA+Gaia analysis pipeline and astrophysical interpretation of the results.

WP Execution Plan 

The INAF research unit leverages the Gaia Italian Data Center (DPCT), one of the most significant astronomical computing facilities in Italy:

• Big Data Management: The DPCT manages approximately 1.5 Petabytes of data, including raw pixels from the astrometric focal plane.

• Supercomputing Integration: The unit utilizes a direct connection to the CINECA supercomputing center to operate global astrometric pipelines.

• GWTracker facility: Creation of the GW tracker infrastructure to implement "extra" scientific procedures designed to detect tiny relativistic effects, such as GW-induced fluctuations, which are not covered by standard mission operations.

The INAF unit carries out its tasks over almost 30 months through the following steps:

1. Infrastructure: Realization of a computing infrastructure at DPCT for data mining and processing.

2. Calibration & Cleaning: Implementing "cleaning" procedures to mitigate instrumental and orbital systematics that could mimic or hide GW signals. Development of an end-to-end pipeline to treat and minimize systematic errors in Gaia data specifically for nHz GW detection.

3. GW astrometric modeling: Developing the mathematical tools to extract GW-induced "glitches" or patterns from the Gaia astrometric residuals. Creation of standalone algorithms to identify GW signals within extracted astrometric residuals. By analyzing the astrometric residuals, we search for the correlation signature characteristic of a stochastic gravitational wave background (GWB). RAMOD’s adaptation to GW is the "mathematical lens" through which Gaia's data is viewed to separate the predictable effects of gravity from the subtle, study of the GW astrometric fingerprints and correlated "noise" produced by nano-Hertz gravitational wave.

4. Synergy: Differential astrometric methods. Spherical harmonic analysis and statistical tools for Gaia data peering. Preparing the next Gaia data (epoch astrometry) in order to be correctly integrated into the joint Bayesian analysis framework. Delivery of a calibrated DR4/DR5 dataset appropriately formatted for the joint timing+astrometry analysis. This will be accomplished as soon as possible once Gaia DR4 is released (by the end of December 2026).

INAF Unit Members 

The INAF-OATo team for GRAPE consists of permanent staff and new dedicated researcher fellowships:  Volodymir Akhemanatov, Ummi Abbas, Beatrice Bucciarelli, Deborah Busonero, Mariateresa Crosta (PI for the INAF-OATo Research Unit), Lorenzo Filipello, Mario Gilberto Lattanzi, Enrico Licata, Federica Santucci.

Related Scientific Resources

·  General relativistic observable for gravitational astrometry in the context of the Gaia mission and beyond (Crosta et al. 2017, Physical Review D, 96, 104030).

·  The global sphere reconstruction (GSR): Demonstrating an independent implementation of the astrometric core solution for Gaia (Vecchiato et al. 2018, Astronomy & Astrophysics, 618, A44).

·  Astrometry in the 21st century: From Hipparchus to Einstein (Crosta 2019, LA RIVISTA DEL NUOVO CIMENTO, ISSUE 10).

·  Pinpointing gravitational waves via astrometric gravitational wave antenna (Crosta et al. 2024, Scientific Reports, 14, 5074).

·  Pattern functions of the Astrometric Gravitational Wave Antenna (Santucci et al. 2025, Scientific Reports, 15, 32908).

·  Differential astrometry with Gaia .Investigating relativistic light deflection close to Jupiter (Abbas et al. 2022, Astronomy & Astrophysics, 664, A143).

·  Analytical solutions of the RAMOD equations for light propagation in the gravitational field of the Solar System (Crosta et al. 2015, Classical and Quantum Gravity, 32, 165008).